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We have used the transfer matrix (T-matrix) method to calculate the transmission and reflection spectra of a one-dimensional photonic crystal structure with a metallic nanoparticle monolayer insert. We have studied the influence of the monolayer parameters and position on the defect modes for the photonic structure.
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Boron-doped Czochralski (Cz) Si is the most commonly used semiconductor in the fabrication of solar cells. The minority carrier lifetime of boron-doped Cz Si decreases upon exposure to light due to B–O-related defects, which reduce the performance of ~10 9 solar modules worldwide. Using electron paramagnetic resonance (EPR), we have identified the spin-active paramagnetic signatures of this phenomenon and gained insights into its microscopic mechanism. We found a distinct defect signature, which diminished when the degraded sample was annealed. The second signature, a broad magnetic field spectrum, due to the unionized B acceptors, was present in the annealed state but vanished upon light exposure. These observations show that, on degradation, nearly all the ~10 16 cm –3 B atoms in Cz Si complexed with interstitial O atoms, whereas only ~10 12 cm –3 of these complexes created defects that were recombination-active. The formation rate of these recombination-active defects correlated with the decay of the minority carrier lifetime. Furthermore, the line shape parameters linked these defects to both B and O impurities in Cz Si.
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In this paper, the design of a two-dimensional photonic crystal micro-cavity based integrated-optic sensor platform is proposed. The behaviour of designed cavity is analyzed using two-dimensional Finite Difference Time Domain (FDTD) method. The structure is designed by deliberately inserting some defects in a photonic crystal waveguide structure. Proposed structure shows a quality factor (Q) of about 1e5 and the average sensitivity of 500nm/RIU in the wavelength range of 1450 – 1580 nm. Sensing technique is based on the detection of shift in upper-edge cut-off wavelength for a reference signal strength of –10 dB in accordance with the change in refractive index of analyte.
Atomic-scale disorder plays an important role in the chemical and physical properties of oxide materials. The structural flexibility of pyrochlore-type oxides allows for crystal-chemical engineering of these properties. Compositional modification can push pyrochlore oxides toward a disordered defect-fluorite structure with anion Frenkel pair defects that facilitate oxygen migration. The local structure of the long-range average cubic defect-fluorite was recently claimed to consist of randomly arranged orthorhombic weberite-type domains. Here, we show, using low-temperature neutron total-scattering experiments, that this is not the case for Zr-rich defect-fluorites. By analyzing data from the pyrochlore/defect-fluorite Y 2 Sn 2–x Zr x O 7 series using a combination of neutron pair distribution function and big-box modelling, we have differentiated and quantified the relationship between anion sub-lattice disorder and Frenkel defects. These details directly influence the energy landscape for oxygen migration and are crucial for simulations and design of new materials with improved properties.
The authors discuss the use of in situ optical absorption to probe point defect equilibria and kinetics in oxides, with particular attention to thin films and high-temperature measurements evaluating changes in oxygen content. The introduction notes the effect of point defects on oxide behavior, including differences in thin films versus bulk materials, and describes methods to evaluate point defect equilibria and kinetics; advantages of optical absorption among these methods are highlighted. Section 2 provides an overview of how optical absorption and point defect concentrations are related, including various possible structural and electronic origins of defect-mediated absorption changes corresponding to oxygen content changes. Section 3 traces the development of historical understanding of optical absorption in nonstoichiometric oxides and emergence of thin film applications and measurement approaches that resulted. Section 4 details the procedure for determining surface exchange coefficients from optical transmission relaxation measurements and provides specific examples of how this approach uniquely has enabled new insights into thin film surface exchange behavior with and without current collectors. Section 5 provides examples of optically derived diffusivity measurements and comparisons of bulk and thin film defect equilibria. Section 7 outlines potential opportunities and future developments in this area, and Section 7 concludes the manuscript.
Perovskite semiconductors have emerged as a promising class of materials for optoelectronic applications. Their favorable device performances can be partly justified by the defect tolerance that originates from their electronic structure. The effect of this inherent defect tolerance, namely the absence of deep trap states, on the photoluminescence (PL) of perovskite nanocrystals (NCs) is currently not well understood. The PL emission of NCs fluctuates in time according to power law kinetics (PL intermittency, or blinking), a phenomenon that has been explored over the past two decades in a vast array of nanocrystal (NC) materials. The kinetics of the blinking process in perovskite NCs have not been widely explored. Here, PL trajectories of individual orthorhombic cesium lead bromide (CsPbBr 3 ) perovskite NCs are measured using a range of excitation intensities. The power law kinetics of the bright NC state are observed to truncate exponentially at long durations, with a truncation time that decreases with increasing intensity before saturating at an intensity corresponding to an average formation of a single exciton. The results indicate that a diffusion-controlled electron transfer (DCET) mechanism is the most likely charge trapping process, while Auger autoionization plays a lesser role. The relevance of the multiple recombination centers (MRC) model to the results presented here cannot be ascertained, since the underlying switching mechanism is not currently available. Further experimentation and theoretical work are needed to gain a comprehensive understanding of the photophysics in these emerging materials.
Here, we report on nm-scale electrical potential imaging throughout As-doped and Cu-doped CdSeTe absorbers using Kelvin probe force microscopy (KPFM). The potential imaging was conducted both laterally and vertically on beveled films using ion milling at small glancing angle. KPFM images electrical potential on the beveled surface and assesses defect charging in the subsurface region within a screening length from the beveled surface. We found that the grain boundaries were positively charged and that there were significant potential fluctuations in both grain boundary versus grain interior and intragrain. We further found that these potential fluctuations decreased significantly toward the front interface. Time of flight secondary ion mass spectrometry imaging shows that Se content increased toward the front interface, consistent with Se passivation of defects. The potential fluctuation was induced by defect charging, and the results elucidate different details of the defect configurations and grain structures of the films with different CdCl 2 treatment temperatures in the As-doped CdSeTe. The defect configurations in the region near the front interface can be a main factor contributing to the device performance difference. Our potential imaging provides insights about the defects throughout the absorber films, and shows that the potential fluctuation has a direct correlation to the V oc deficit.
Nucleation, growth and perfection of protein crystals will be overviewed along with crystal mechanical properties. The knowledge is based on experiments using optical and force crystals behave similar to inorganic crystals, though with a difference in orders of magnitude in growing parameters. For example, the low incorporation rate of large biomolecules requires up to 100 times larger supersaturation to grow protein, rather than inorganic crystals. Nucleation is often poorly reproducible, partly because of turbulence accompanying the mixing of precipitant with protein solution. Light scattering reveals fluctuations of molecular cluster size, its growth, surface energies and increased clustering as protein ages. Growth most often occurs layer-by-layer resulting in faceted crystals. New molecular layer on crystal face is terminated by a step where molecular incorporation occurs. Quantitative data on the incorporation rate will be discussed. Rounded crystals with molecularly disordered interfaces will be explained. Defects in crystals compromise the x-ray diffraction resolution crucially needed to find the 3D atomic structure of biomolecules. The defects are immobile so that birth defects stay forever. All lattice defects known for inorganics are revealed in protein crystals. Contribution of molecular conformations to lattice disorder is important, but not studied. This contribution may be enhanced by stress field from other defects. Homologous impurities (e.g., dimers, acetylated molecules) are trapped more willingly by a growing crystal than foreign protein impurities. The trapped impurities induce internal stress eliminated in crystals exceeding a critical size (part of mni for ferritin, lysozyme). Lesser impurities are trapped from stagnant, as compared to the flowing, solution. Freezing may induce much more defects unless quickly amorphysizing intracrystalline water.
Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which has the capability of melting metallic powder and net shaping the structures with relatively high precision. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to creep in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures nondestructively. Pulsed Thermography (PT) imaging provides a capability for non-destructive evaluation (NDE) of sub-surface defects in arbitrary size structures. The PT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. The data cube of PT measurements consists of surface temperature taken at sequential time intervals T(x,y,t). Material defects can be detected either by analyzing the thermograms T(x,y,t) data cube, or by using thermal tomography (TT) algorithm to obtain 3D spatial reconstruction of thermal effusivity e(x,y,z). To reduce the cost and enable in-service NDE in spatially constrained environment, it is highly desirable to develop PT with compact and inexpensive IR camera. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact PT system can also be used for in-service nondestructive evaluation (NDE) applications. However, data cube obtained with PT based on compact IR camera suffers from strong thermal noises and loss of features due to relatively low sampling rate. In this report we describe two unsupervised machine learning (ML) algorithms for enhancement of PT images obtained with compact IR camera. In one approach, we introduce Sparse Coding Discrete Cosine Transform (SC/DCT) algorithm to remove additive white Gaussian noise (AWGN) from spatial thermal effusivity reconstructions. In another approach we introduce a Spatial Temporal Denoised Thermal Source Separation (STDTSS) ML algorithm to process thermograms. The STDTSS algorithm consists of spatial and temporal denoising using Gaussian and Savitzky–Golay filtering, followed by the matrix decomposition using Principal Component Analysis (PCA), and Independent Component Analysis (ICA) to automatically detect flaws. In the work described in this report, we constructed a compact PT system using a relatively small and low-cost FLIR A65 camera, consisting on uncooled microbolometer detector. Performance of SC/DCT algorithm was demonstrated on enhancing TT images of Inconel 718 AM plate. Performance of the STDTSS methods was investigated using thermography data obtained from imaging stainless steel 316L specimens produced with LPBF method with imprinted calibrated porosity defects.
Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which has the capability of melting metallic powder and net shaping the structures with relatively high precision. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermography Imaging (PTI) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTI method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTI method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTI system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTI capabilities in detecting microscopic defects in metallic specimens. SS316 and IN718 specimens were developed with a pattern of subsurface calibrated flat bottom hole (FBH) defects with diameters from 500µm to 200µm. FBH’s were created with EDM (electron discharge machining) drill. PTI imaging data was processed Spatial Temporal Denoised Thermal Source Separation (STDTSS) unsupervised machine learning (ML) algorithm. We show that defects as small as 200µm in SS316 and IN718 can be detected with STDTSS algorithm. To the best of our knowledge, these are the smallest detected defects which are reported in literature.
Based on two issued US patent, US7947579B2 and US8187678B2 that were invented by our team member at the University of New Mexico and Sandia National Labs, using atomic layer deposition technique (ALD) and molecular self-assembly or templating technique, An ultra-thin CO 2 membrane with CO 2 permeance up to 1580 GPU and CO 2 /N 2 up to 62 has been achieved in phase I project, promising for cost-effective CO 2 separations. As the first step of the project, a robust membrane fabrication protocol was established. To address the defects in the membrane structure, ALD treatment on AO support, multiple dip-coating processes and slow calcination steps were adopted. Consequently, defects were no longer evident in the nanoporous support, which ensures a reliable procedure for lab-scale membrane fabrications as well as the high-fidelity experimental findings. The same procedures may also be helpful for future scaling-up protocols. The layer-by-layer membrane fabrication was started by using a bridged disilane BTEE as the ALD precursor, wherein the organic groups at the bridging site were expected to be aligned layer-by-layer to form Angstrom-channels for CO 2 transport. Using 2-level factorial experimental design, we have found that ALD reaction time and ALD temperature were important factors impacting the CO 2 permeance and selectivity. Longer reaction time and higher ALD temperature were found to be advantageous for better CO 2 permeance and selectivity, which is in agreement with our model that better-aligned CO 2 -channels formed by the layer-by-layer stacking of the organic ligands can be achieved by a slower “stacking” process (longer reaction time) and stronger self-alignment tendency (higher ALD temperature). This observation will be an important guidance for our future membrane designs. The CO 2 -channel templated by –(CH 2 ) 2 - in BTEE was found to be too tight to facilitate fast CO 2 transport, but larger channel diameter is in contradiction with higher CO 2 selectivity. Therefore, the size-exclusion mechanism by itself is not sufficient for effective CO 2 separation. For this reason, the chemistry of the CO 2 -channel has to be carefully tuned. An amine bridged-disilane BTMA was therefore used as ALD precursor for larger CO 2 channel and high CO 2 -affinity chemistry. For BMTA membrane with amine chemistry measured at 100C, the CO 2 permeance was 1030 GPU for 100-cycle-ALD sample with CO 2 /N 2 selectivity of 17, and 302 GPU for 200-cycle-ALD sample with CO 2 /N 2 selectivity of 44. The increase of CO 2 permeance and the CO 2 /N 2 selectivity at elevated temperature is an evidence showing that there is a preferential chemical interaction between CO 2 and –NH functional groups in the membrane, which facilitates selective transport of CO 2 through the membrane. Therefore, using larger organic ligands as the CO 2 -channel template and the introduction of –NH chemistry to the membrane structure were proved to be an effective strategy in achieving better CO 2 permeance and selectivity. Guided by the same strategy, BTMA membrane was irradiated with UV to remove the bridging ligands for larger CO-channel, followed by Zn 2+ and Ni 2+ chemistry modification. Results showed that Zn 2+ or Ni 2+ chemistries will both enhance the selective CO 2 transport thereby the CO 2 /N 2 selectivity, and increasing separation temperature will further improve the CO2 permeance and selectivity. For BTMA membrane with Ni 2+ chemistry measured at 100C, CO 2 permeance of 1580 GPU and CO 2 /N 2 of 62 were achieved, promising for scaled-up industrial applications. Further, same membrane was tested at simulated flue gas condition (with SO 2 at 60C), the CO 2 permeance was 920 GPU and the CO 2 /N 2 selectivity was 52, suggesting the membrane still worked well under simulated flue gas conditions, primarily due to the stable ceramic framework of this membrane.